code: def boxplot_frame_groupby(
      grouped: DataFrameGroupBy,
      subplots: bool = True,
      column=None,
      fontsize: int | None = None,
      rot: int = 0,
      grid: bool = True,
      ax=None,
      figsize: tuple[float, float] | None = None,
      layout=None,
      sharex: bool = False,
      sharey: bool = True,
      backend=None,
      **kwargs,
  ):
      """
      Make box plots from DataFrameGroupBy data.
  
      Parameters
      ----------
      grouped : Grouped DataFrame
      subplots : bool
          * ``False`` - no subplots will be used
          * ``True`` - create a subplot for each group.
  
      column : column name or list of names, or vector
          Can be any valid input to groupby.
      fontsize : float or str
      rot : label rotation angle
      grid : Setting this to True will show the grid
      ax : Matplotlib axis object, default None
      figsize : A tuple (width, height) in inches
      layout : tuple (optional)
          The layout of the plot: (rows, columns).
      sharex : bool, default False
          Whether x-axes will be shared among subplots.
      sharey : bool, default True
          Whether y-axes will be shared among subplots.
      backend : str, default None
          Backend to use instead of the backend specified in the option
          ``plotting.backend``. For instance, 'matplotlib'. Alternatively, to
          specify the ``plotting.backend`` for the whole session, set
          ``pd.options.plotting.backend``.
      **kwargs
          All other plotting keyword arguments to be passed to
          matplotlib's boxplot function.
  
      Returns
      -------
      dict of key/value = group key/DataFrame.boxplot return value
      or DataFrame.boxplot return value in case subplots=figures=False
  
      Examples
      --------
      You can create boxplots for grouped data and show them as separate subplots:
  
      .. plot::
          :context: close-figs
  
          >>> import itertools
          >>> tuples = [t for t in itertools.product(range(1000), range(4))]
          >>> index = pd.MultiIndex.from_tuples(tuples, names=['lvl0', 'lvl1'])
          >>> data = np.random.randn(len(index), 4)
          >>> df = pd.DataFrame(data, columns=list('ABCD'), index=index)
          >>> grouped = df.groupby(level='lvl1')
          >>> grouped.boxplot(rot=45, fontsize=12, figsize=(8, 10))  # doctest: +SKIP
  
      The ``subplots=False`` option shows the boxplots in a single figure.
  
      .. plot::
          :context: close-figs
  
          >>> grouped.boxplot(subplots=False, rot=45, fontsize=12)  # doctest: +SKIP
      """
      plot_backend = _get_plot_backend(backend)
      return plot_backend.boxplot_frame_groupby(
          grouped,
          subplots=subplots,
          column=column,
          fontsize=fontsize,
          rot=rot,
          grid=grid,
          ax=ax,
          figsize=figsize,
          layout=layout,
          sharex=sharex,
          sharey=sharey,
          **kwargs,
      )
  
imports: from __future__ import annotations
  import importlib
  from typing import TYPE_CHECKING, Callable, Literal
  from pandas._config import get_option
  from pandas.util._decorators import Appender, Substitution
  from pandas.core.dtypes.common import is_integer, is_list_like
  from pandas.core.dtypes.generic import ABCDataFrame, ABCSeries
  from pandas.core.base import PandasObject
label_desc: Use image node_id 5 for calling a global function with example usage: boxplot_frame_groupby(grouped, subplots, column, fontsize, rot, grid, ax, figsize, layout, sharex, sharey, backend) and returns: plot_backend